Zobrazeno 1 - 10
of 27
pro vyhledávání: '"Păiș, Vasile"'
Autor:
Avram, Andrei-Marius, Iuga, Andreea, Manolache, George-Vlad, Matei, Vlad-Cristian, Micliuş, Răzvan-Gabriel, Muntean, Vlad-Andrei, Sorlescu, Manuel-Petru, Şerban, Dragoş-Andrei, Urse, Adrian-Dinu, Păiş, Vasile, Cercel, Dumitru-Clementin
This work introduces HistNERo, the first Romanian corpus for Named Entity Recognition (NER) in historical newspapers. The dataset contains 323k tokens of text, covering more than half of the 19th century (i.e., 1817) until the late part of the 20th c
Externí odkaz:
http://arxiv.org/abs/2405.00155
Autor:
Avram, Andrei-Marius, Smădu, Răzvan-Alexandru, Păiş, Vasile, Cercel, Dumitru-Clementin, Ion, Radu, Tufiş, Dan
With the rise of bidirectional encoder representations from Transformer models in natural language processing, the speech community has adopted some of their development methodologies. Therefore, the Wav2Vec models were introduced to reduce the data
Externí odkaz:
http://arxiv.org/abs/2306.17792
Autor:
Avram, Andrei-Marius, Mititelu, Verginica Barbu, Păiş, Vasile, Cercel, Dumitru-Clementin, Trăuşan-Matu, Ştefan
Correctly identifying multiword expressions (MWEs) is an important task for most natural language processing systems since their misidentification can result in ambiguity and misunderstanding of the underlying text. In this work, we evaluate the perf
Externí odkaz:
http://arxiv.org/abs/2306.10419
Autor:
Ion, Radu, Avram, Andrei-Marius, Păiş, Vasile, Mitrofan, Maria, Mititelu, Verginica Barbu, Irimia, Elena, Badea, Valentin
The paper presents an open-domain Question Answering system for Romanian, answering COVID-19 related questions. The QA system pipeline involves automatic question processing, automatic query generation, web searching for the top 10 most relevant docu
Externí odkaz:
http://arxiv.org/abs/2206.08046
Autor:
Avram, Andrei-Marius, Catrina, Darius, Cercel, Dumitru-Clementin, Dascălu, Mihai, Rebedea, Traian, Păiş, Vasile, Tufiş, Dan
Running large-scale pre-trained language models in computationally constrained environments remains a challenging problem yet to be addressed, while transfer learning from these models has become prevalent in Natural Language Processing tasks. Severa
Externí odkaz:
http://arxiv.org/abs/2112.12650
Autor:
Dhole, Kaustubh D., Gangal, Varun, Gehrmann, Sebastian, Gupta, Aadesh, Li, Zhenhao, Mahamood, Saad, Mahendiran, Abinaya, Mille, Simon, Shrivastava, Ashish, Tan, Samson, Wu, Tongshuang, Sohl-Dickstein, Jascha, Choi, Jinho D., Hovy, Eduard, Dusek, Ondrej, Ruder, Sebastian, Anand, Sajant, Aneja, Nagender, Banjade, Rabin, Barthe, Lisa, Behnke, Hanna, Berlot-Attwell, Ian, Boyle, Connor, Brun, Caroline, Cabezudo, Marco Antonio Sobrevilla, Cahyawijaya, Samuel, Chapuis, Emile, Che, Wanxiang, Choudhary, Mukund, Clauss, Christian, Colombo, Pierre, Cornell, Filip, Dagan, Gautier, Das, Mayukh, Dixit, Tanay, Dopierre, Thomas, Dray, Paul-Alexis, Dubey, Suchitra, Ekeinhor, Tatiana, Di Giovanni, Marco, Goyal, Tanya, Gupta, Rishabh, Hamla, Louanes, Han, Sang, Harel-Canada, Fabrice, Honore, Antoine, Jindal, Ishan, Joniak, Przemyslaw K., Kleyko, Denis, Kovatchev, Venelin, Krishna, Kalpesh, Kumar, Ashutosh, Langer, Stefan, Lee, Seungjae Ryan, Levinson, Corey James, Liang, Hualou, Liang, Kaizhao, Liu, Zhexiong, Lukyanenko, Andrey, Marivate, Vukosi, de Melo, Gerard, Meoni, Simon, Meyer, Maxime, Mir, Afnan, Moosavi, Nafise Sadat, Muennighoff, Niklas, Mun, Timothy Sum Hon, Murray, Kenton, Namysl, Marcin, Obedkova, Maria, Oli, Priti, Pasricha, Nivranshu, Pfister, Jan, Plant, Richard, Prabhu, Vinay, Pais, Vasile, Qin, Libo, Raji, Shahab, Rajpoot, Pawan Kumar, Raunak, Vikas, Rinberg, Roy, Roberts, Nicolas, Rodriguez, Juan Diego, Roux, Claude, S., Vasconcellos P. H., Sai, Ananya B., Schmidt, Robin M., Scialom, Thomas, Sefara, Tshephisho, Shamsi, Saqib N., Shen, Xudong, Shi, Haoyue, Shi, Yiwen, Shvets, Anna, Siegel, Nick, Sileo, Damien, Simon, Jamie, Singh, Chandan, Sitelew, Roman, Soni, Priyank, Sorensen, Taylor, Soto, William, Srivastava, Aman, Srivatsa, KV Aditya, Sun, Tony, T, Mukund Varma, Tabassum, A, Tan, Fiona Anting, Teehan, Ryan, Tiwari, Mo, Tolkiehn, Marie, Wang, Athena, Wang, Zijian, Wang, Gloria, Wang, Zijie J., Wei, Fuxuan, Wilie, Bryan, Winata, Genta Indra, Wu, Xinyi, Wydmański, Witold, Xie, Tianbao, Yaseen, Usama, Yee, Michael A., Zhang, Jing, Zhang, Yue
Data augmentation is an important component in the robustness evaluation of models in natural language processing (NLP) and in enhancing the diversity of the data they are trained on. In this paper, we present NL-Augmenter, a new participatory Python
Externí odkaz:
http://arxiv.org/abs/2112.02721
One of the fundamental functionalities for accepting a socially assistive robot is its communication capabilities with other agents in the environment. In the context of the ROBIN project, situational dialogue through voice interaction with a robot w
Externí odkaz:
http://arxiv.org/abs/2111.12028
Autor:
Păiş, Vasile, Ion, Radu, Avram, Andrei-Marius, Irimia, Elena, Mititelu, Verginica Barbu, Mitrofan, Maria
Publikováno v:
V. P\u{a}i\c{s}, R. Ion, A. -M. Avram, E. Irimia, V. B. Mititelu and M. Mitrofan, "Human-Machine Interaction Speech Corpus from the ROBIN project", Proceedings SpeD, 2021, pp. 91-96
This paper introduces a new Romanian speech corpus from the ROBIN project, called ROBIN Technical Acquisition Speech Corpus (ROBINTASC). Its main purpose was to improve the behaviour of a conversational agent, allowing human-machine interaction in th
Externí odkaz:
http://arxiv.org/abs/2111.11170
Autor:
Păiş, Vasile, Tufiş, Dan
Publikováno v:
P\u{a}i\c{s}, Vasile and Tufi\c{s}, Dan. More Romanian word embeddings from the RETEROM project. In Proceedings of the International Conference on Linguistic Resources and Tools for Processing Romanian Language - CONSILR. pp. 91-100, 2018
Automatically learned vector representations of words, also known as "word embeddings", are becoming a basic building block for more and more natural language processing algorithms. There are different ways and tools for constructing word embeddings.
Externí odkaz:
http://arxiv.org/abs/2111.10750